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SECURE IMAGE STEGANOGRAPHY USING ECC AND CHACHA20 WITH COMPRESSION
Embedding secret data within digital images (steganography) is a widely used technique for covert communication. However, traditional LSB methods lack confidentiality and integrity checks, making them vulnerable to extraction and tampering. To address these shortcomings, this work proposes an integrated solution that combines encryption (ECC or ChaCha20), LSB steganography, and compression to securely hide short payloads inside cover images. Public-key cryptography offers strong security but can be computationally intensive, whereas symmetric stream ciphers like ChaCha20 deliver high performance but require key distribution. Conventional LSB steganography directly embeds plaintext bits, exposing messages to steganalysis and eavesdropping. A robust system is therefore needed to ensure that extracted data cannot be read without the key, and that any alteration is detectable. In this project, the secret message is first encrypted using either ECIES over secp256k1 (asymmetric) or ChaCha20 (symmetric), and its SHA-256 hash is computed to ensure integrity. The resulting ciphertext bytes are Base64-encoded and converted into an ASCII bitstream, which is then embedded into the least significant bits of an RGB image. The stego image is subsequently compressed using zlib to reduce file size and obscure potential embedding artifacts. On the receiver side, the compressed file is decompressed, the LSB bits are extracted to reconstruct the Base64 ciphertext, the SHA-256 hash is recalculated to verify integrity, and the payload is decrypted. A Tkinter GUI guides users through uploading images, entering secrets, selecting encryption modes, and viewing performance graphs that compare ECC and ChaCha20. Experimental results show that ChaCha20 encryption is significantly faster than ECC for short messages, while ECC provides asymmetric security without the need for key exchange. By integrating strong encryption, steganography, and compression, this system mitigates the limitations of traditional LSB methods— ensuring confidentiality, integrity, and minimal perceptual distortion—making it well-suited for applications requiring covert, tamper-evident communication
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